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A flexible extreme value mixture model

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  1. Fátima Brilhante, M. & Ivette Gomes, M. & Pestana, Dinis, 2013. "A simple generalisation of the Hill estimator," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 518-535.
  2. Wendy Shinyie & Noriszura Ismail & Abdul Jemain, 2014. "Semi-parametric Estimation Based on Second Order Parameter for Selecting Optimal Threshold of Extreme Rainfall Events," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(11), pages 3489-3514, September.
  3. Schaumburg, Julia, 2012. "Predicting extreme value at risk: Nonparametric quantile regression with refinements from extreme value theory," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4081-4096.
  4. André, L.M. & Wadsworth, J.L. & O'Hagan, A., 2024. "Joint modelling of the body and tail of bivariate data," Computational Statistics & Data Analysis, Elsevier, vol. 189(C).
  5. Philémon Gamet & Jonathan Jalbert, 2022. "A flexible extended generalized Pareto distribution for tail estimation," Environmetrics, John Wiley & Sons, Ltd., vol. 33(6), September.
  6. Caston Sigauke & Rosinah Mukhodobwane & Wilbert Chagwiza & Winston Garira, 2022. "Asymptotic Dependence Modelling of the BRICS Stock Markets," IJFS, MDPI, vol. 10(3), pages 1-32, July.
  7. So, Mike K.P. & Chan, Raymond K.S., 2014. "Bayesian analysis of tail asymmetry based on a threshold extreme value model," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 568-587.
  8. Chiara Lattanzi & Manuele Leonelli, 2019. "A changepoint approach for the identification of financial extreme regimes," Papers 1902.09205, arXiv.org.
  9. Sonia Benito & Carmen López-Martín & Mª Ángeles Navarro, 2023. "Assessing the importance of the choice threshold in quantifying market risk under the POT approach (EVT)," Risk Management, Palgrave Macmillan, vol. 25(1), pages 1-31, March.
  10. D. J. Rasmussen & Scott Kulp & Robert E. Kopp & Michael Oppenheimer & Benjamin H. Strauss, 2022. "Popular extreme sea level metrics can better communicate impacts," Climatic Change, Springer, vol. 170(3), pages 1-17, February.
  11. Shafique Ur Rehman & Touqeer Ahmad & Wu Dash Desheng & Amirhossein Karamoozian, 2024. "Analyzing selected cryptocurrencies spillover effects on global financial indices: Comparing risk measures using conventional and eGARCH-EVT-Copula approaches," Papers 2407.15766, arXiv.org.
  12. Kaouther Toumi & Jean-Laurent Viviani & Zeinab Chayeh, 2019. "Measurement of the displaced commercial risk in Islamic Banks," Post-Print halshs-01806496, HAL.
  13. Dadalau Diana, 2012. "Integrated Estimation Model Of The Difficulty Status Of Entreprise," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 4, pages 130-143, December.
  14. Gbari, Kock Yed Ake Samuel & Poulain, Michel & Dal, Luc & Denuit, Michel, 2016. "Extreme value analysis of mortality at the oldest ages: a case study based on individual ages at death," LIDAM Discussion Papers ISBA 2016012, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  15. Sigauke, Caston & Bere, Alphonce, 2017. "Modelling non-stationary time series using a peaks over threshold distribution with time varying covariates and threshold: An application to peak electricity demand," Energy, Elsevier, vol. 119(C), pages 152-166.
  16. Paul J. Northrop & Nicolas Attalides & Philip Jonathan, 2017. "Cross-validatory extreme value threshold selection and uncertainty with application to ocean storm severity," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 93-120, January.
  17. Toumi, Kaouther & Viviani, Jean-Laurent & Chayeh, Zeinab, 2019. "Measurement of the displaced commercial risk in Islamic Banks," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 18-31.
  18. Yingjie Wang & Xinsheng Liu, 2022. "A New Point Process Regression Extreme Model Using a Dirichlet Process Mixture of Weibull Distribution," Mathematics, MDPI, vol. 10(20), pages 1-24, October.
  19. Erin M. Schliep & Alan E. Gelfand & Jesús Abaurrea & Jesús Asín & María A. Beamonte & Ana C. Cebrián, 2021. "Long‐term spatial modelling for characteristics of extreme heat events," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 1070-1092, July.
  20. Muhammad Hilmi Abdul Majid & Kamarulzaman Ibrahim, 2021. "On Bayesian approach to composite Pareto models," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-22, September.
  21. Lee, J. & Fan, Y. & Sisson, S.A., 2015. "Bayesian threshold selection for extremal models using measures of surprise," Computational Statistics & Data Analysis, Elsevier, vol. 85(C), pages 84-99.
  22. M. Carvalho & S. Pereira & P. Pereira & P. Zea Bermudez, 2022. "An Extreme Value Bayesian Lasso for the Conditional Left and Right Tails," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 222-239, June.
  23. Sigauke, Caston & Verster, Andréhette & Chikobvu, Delson, 2013. "Extreme daily increases in peak electricity demand: Tail-quantile estimation," Energy Policy, Elsevier, vol. 53(C), pages 90-96.
  24. Cristiano Villa, 2017. "Bayesian estimation of the threshold of a generalised pareto distribution for heavy-tailed observations," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 95-118, March.
  25. Juan Gonzalez & Daniela Rodriguez & Mariela Sued, 2013. "Threshold selection for extremes under a semiparametric model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(4), pages 481-500, November.
  26. Bram Thijssen & Lodewyk F A Wessels, 2020. "Approximating multivariate posterior distribution functions from Monte Carlo samples for sequential Bayesian inference," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-25, March.
  27. Fernando Nascimento & Dani Gamerman & Hedibert Lopes, 2016. "Time-varying extreme pattern with dynamic models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 131-149, March.
  28. Dhanushi A. Wijeyakulasuriya & Ephraim M. Hanks & Benjamin A. Shaby & Paul C. Cross, 2019. "Extreme Value-Based Methods for Modeling Elk Yearly Movements," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(1), pages 73-91, March.
  29. Semeyutin, Artur & O’Neill, Robert, 2019. "A brief survey on the choice of parameters for: “Kernel density estimation for time series data”," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
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